1. Field of the Invention
The invention relates generally to the field of medical imaging. More particularly, the invention relates to phase sensitive magnetic resonance imaging using an efficient and robust image processing algorithm.
2. Discussion of the Related Art
Magnetic resonance imaging (MRI) has proven useful in the diagnosis of many diseases such as hepatic steatosis, cancer, multiple sclerosis, sports related injury, and bone marrow disorders. MRI provides unique imaging capabilities which are not attainable in any other imaging method. For example, MRI can provide detailed images of soft tissues, abnormal tissues such as tumors, and other structures which cannot be readily imaged using techniques like X-rays. Further, MRI operates without exposing patients to ionizing radiation experienced in X-rays. For these and other reasons, MRI is commonly utilized in the medical field.
In comparison to other imaging modalities, MRI is unique in that the MRI signal is represented by a complex number, rather than simply a scalar (such as X-ray attenuation in CT). The image value for each image pixel, therefore, usually includes a magnitude and a phase. Although the phase of an image pixel may carry important information and may be used in many applications such as chemical shift imaging, thermal imaging, and blood flow quantization, it is usually discarded in the standard image reconstruction process. The underlying reason is that some unwanted error phase almost always accompanies the desired phase. Although many methods have been developed to remove the error phase, a truly reliable and automated phase correction method is still lacking.
One application for phase correction of MR images includes inversion recovery imaging. Inversion recovery (IR) is generally used as a magnetization preparation technique in MRI. In IR imaging, the longitudinal magnetization along the main magnetic field is first rotated to the opposite direction using a 180° radiofrequency (RF) pulse. The inverted magnetization can be recovered by T1 relaxation during an inversion time (T1) between the inversion and the excitation RF pulses. One example application of the IR imaging is for suppression of a given type of tissue with a characteristic T1, such as short-tau inversion recovery (STIR) for fat suppression or fluid-attenuated inversion recovery (FLAIR) for cerebral spinal fluid attenuation. Another example application of IR imaging is for increased tissue contrast from the doubling of the dynamic range of the longitudinal magnetization. The application could be useful for imaging of neonate brains, myocardium at delayed enhancement, and for evaluating pulmonary blood flow. The potential for increased tissue contrast by IR imaging, however, is not always realized because conventional MR image reconstruction preserves only the magnitude of the MR signals and may actually lead to reduced or even reversed contrast in an IR image.
Phase-sensitive IR (PSIR) image reconstruction, in which unwanted phase errors in an IR image are removed, is a technique that can restore the contrast loss or reversal resulting from conventional magnitude image reconstruction. The main challenge in PSIR image reconstruction is a phase-correction process to separate the intrinsic signal phase in the complex image from other phase errors, which are common in an MR image. Several approaches have been proposed for PSIR image reconstruction including calibration of the phase errors through acquisition of another image without IR or with IR at different TIs. However, these approaches reduce data acquisition efficiency. Further, spatial misregistration between the actual and calibration scans due to patient motion can also be problematic.
An alternative approach for PSIR image reconstruction is to determine the phase errors from the IR image itself using various phase correction algorithms. In general, only the signal phase of a neighbor pixel for overall phase correction is used. As such, pixels with large phase variation, such as in regions of low signal-to-noise ratio (SNR) or along tissue boundaries may corrupt the phase correction process. In order to minimize the effect, an empirical threshold is usually selected to exclude regions of large phase uncertainty. The actual threshold value, however, can be critical. If the value selected is too small, phase correction cannot reach beyond the regions defined by the threshold value and may thus be terminated prematurely. Alternatively, if the value selected is too large, errors in phase correction may propagate and even corrupt the rest of the process. In a region growing-based approach, for example, the selection of the threshold value together with that of the initial seed and the path of the region growing, determines the quality and the scope of the phase correction. To allow phase correction to proceed beyond local phase fluctuations and to avoid potential corruption due to phase correction errors, an additional special treatment, such as a “bridge filter” is required. Another limitation of the phase correction algorithms is the global polarity of a PSIR image, which cannot be unambiguously determined from the phase correction process itself. Consequently, images from different component channels of a phased array coil cannot be readily combined and inconsistency in display may arise for different images of a multi-slice acquisition.
Another application where correction of phase errors is important is the Dixon chemical shift imaging technique. In MRI, the signal-emitting protons may resonate at different Larmor frequencies because they have different local molecular environments or chemical shift. The two most distinct species found in the human body are water and fat, whose Larmor frequencies are separated by about 3.5 ppm (parts per million). In many clinical MRI applications, it is desirable to suppress signals from fat because they are usually very bright and obscure lesions. Presently, the most commonly used method for fat suppression is chemical shift selective saturation (CHESS), which, despite its many advantages, is known to be intrinsically susceptible to both the radiofrequency (RF) and the magnetic field inhomogeneity. Another technique that is sometimes used for fat suppression is the short tau inversion recovery (STIR), which is based on the characteristically short T1 relaxation constant for fat, rather than on its Larmor frequency. The drawbacks of STIR include reduction in scan efficiency and signal-to-noise ratio as well as potential alteration to the image contrast.
The referenced need for phase corrections in MRI and shortcomings of some of the existing approaches are not intended to be exhaustive, but rather are among many that tend to impair the effectiveness of previously known techniques concerning image reconstruction; however, those mentioned here are sufficient to demonstrate that the methodologies appearing in the art have not been satisfactory and that a significant need exists for the techniques described and claimed in this disclosure.